Conditional generative adversarial network for 3D rigid-body motion correction in MRI.

CONCLUSION: The images predicted by the conditional generative adversarial network have quantitatively and qualitatively improved image quality compared to the motion-corrupted images. PMID: 31006909 [PubMed - as supplied by publisher]

https://www.ncbi.nlm.nih.gov/pubmed/31006909?dopt=Abstract

Source: Magnetic Resonance in Medicine - April 21, 2019 Category: Radiology Authors: Johnson PM, Drangova M Tags: Magn Reson Med Source Type: research

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